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Teradata MCP Server

Official
by Teradata
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Python
Remote

Base Tablepreview

base_tablePreview
Read-onlyIdempotent

Preview the first rows of any Teradata table or view without writing SQL. Quickly inspect sample data to understand its structure and contents.

Instructions

Return a quick sample of the first few rows from a Teradata table or view so the user can see what data looks like, with no SQL required. Use this tool when the user wants to explore or peek at a table's contents without specifying conditions or writing a query. Do NOT use when the user provides a WHERE clause, filter, or explicit SQL statement — use base_readQuery for that.

Arguments: table_name - Table or view name database_name - Database name persist - If True, materializes result as a volatile table and returns table name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
persistNoIf True, materializes result as a volatile table and returns table name
table_nameYesTable or view name
database_nameNoDatabase name

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed9 schema fields changedv0.2.1
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / database_name / anyOf
      Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]
    • changedInput schema / properties / database_name / default
      Previous value: -nullNew value: +""
    • addedInput schema / properties / database_name / description
      Added value: +"Database name"
    • removedInput schema / properties / database_name / title
      Removed value: -"Database Name"
    • addedInput schema / properties / database_name / type
      Added value: +"string"
    • addedInput schema / properties / persist
      Added value: +{
+  "default": false,
+  "description": "If True, materializes result as a volatile table and returns table name",
+  "type": "boolean"
+}
    • addedInput schema / properties / table_name / description
      Added value: +"Table or view name"
    • removedInput schema / properties / table_name / title
      Removed value: -"Table Name"
  2. Changed1 schema field changedv1.0.0
    • removedInput schema / title
      Removed value: -"handle_base_tablePreviewArguments"
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description's main pulse for behavior is safe. The description goes further by explaining the persist option materializes a volatile table and returns the table name, as well as clarifying that no SQL is required. It doesn't disclose the exact row limit or response format, but the core behavior is well covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description leads with the purpose, then gives usage guidance, and then lists arguments. It is well-organized but the 'Arguments' section duplicates the input schema with no added detail. Still, it is a compact length and front-loaded with the most actionable information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple preview tool, the description covers what it does, when to use it, and the significant persist side effect. Though no output schema exists, the description hints it returns rows and possibly a table name. It doesn't explicitly mention the number of rows or response format, which is a minor gap but overall adequate for an agent to safely invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters. The description reproduces the parameter names and short descriptions but adds no new semantics beyond the schema (e.g., it doesn't explain row limit, table naming rules, or edge cases). Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Return a quick sample of the first few rows') on a specific resource (Teradata table or view), and explicitly distinguishes it from base_readQuery by noting the lack of SQL/filter usage. This clearly sets it apart from siblings like base_readQuery and base_tableList.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit 'when to use' ('explore or peek at a table's contents without specifying conditions') and 'when not to use' (the user provides WHERE clause, filter, or explicit SQL) conditions, naming the alternative tool (base_readQuery).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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